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Automatic Speech Recognition (ASR)

Automatic Speech Recognition (ASR) involves converting spoken language into written text. It is designed to transcribe spoken words into text in real-time, allowing people to communicate with computers, mobile devices, and other technology using their voice. The goal of Automatic Speech Recognition is to accurately transcribe speech, taking into account variations in accent, pronunciation, and speaking style, as well as background noise and other factors that can affect speech quality.

Papers

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Showing 1401–1425 of 3012 papers

TitleStatusHype
Extracting Domain Invariant Features by Unsupervised Learning for Robust Automatic Speech Recognition—0
Extracting Biomedical Entities from Noisy Audio Transcripts—0
BUT System for the MLC-SLM Challenge—0
Improved Consistency Training for Semi-Supervised Sequence-to-Sequence ASR via Speech Chain Reconstruction and Self-Transcribing—0
Improved Contextual Recognition In Automatic Speech Recognition Systems By Semantic Lattice Rescoring—0
Improved far-field speech recognition using Joint Variational Autoencoder—0
Extending Recurrent Neural Aligner for Streaming End-to-End Speech Recognition in Mandarin—0
Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training—0
Improved Mask-CTC for Non-Autoregressive End-to-End ASR—0
BUT Opensat 2019 Speech Recognition System—0
Improved Robustness to Disfluencies in RNN-Transducer Based Speech Recognition—0
Improved Self-Supervised Multilingual Speech Representation Learning Combined with Auxiliary Language Information—0
Improved Speech Pre-Training with Supervision-Enhanced Acoustic Unit—0
Improved Training Techniques for Online Neural Machine Translation—0
Improved Transcription and Indexing of Oral History Interviews for Digital Humanities Research—0
Improve Sinhala Speech Recognition Through e2e LF-MMI Model—0
A Probabilistic Framework for Representing Dialog Systems and Entropy-Based Dialog Management through Dynamic Stochastic State Evolution—0
Improving Accented Speech Recognition with Multi-Domain Training—0
Extended Graph Temporal Classification for Multi-Speaker End-to-End ASR—0
Improving accuracy of rare words for RNN-Transducer through unigram shallow fusion—0
Exponentially Decaying Bag-of-Words Input Features for Feed-Forward Neural Network in Statistical Machine Translation—0
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline—0
Exploring WavLM Back-ends for Speech Spoofing and Deepfake Detection—0
Improving Black-box Speech Recognition using Semantic Parsing—0
Exploring Transfer Learning For End-to-End Spoken Language Understanding—0
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All datasetsLRS2RealMANSagaleeHUI speech corpusLRS3-TEDM-AILabs speech datasetThe Spoken Wikipedia CorporaVoxforge GermanVoxPopuli

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TM-CTCTest WER10.1—Unverified
2TM-seq2seqTest WER9.7—Unverified
3CTC/attentionTest WER8.2—Unverified
4LF-MMI TDNNTest WER6.7—Unverified
5Whisper-LLaMATest WER6.6—Unverified
6End2end ConformerTest WER3.9—Unverified
7End2end ConformerTest WER3.7—Unverified
8MoCo + wav2vec (w/o extLM)Test WER2.7—Unverified
9CTC/AttentionTest WER1.5—Unverified
10WhisperTest WER1.3—Unverified
#ModelMetricClaimedVerifiedStatus
1SpatialNetCER14.5—Unverified
2CleanMel-L-maskCER14.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ConformerTest WER15.32—Unverified
2Whisper-largev3-finetunedTest WER10.82—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)1.89—Unverified
#ModelMetricClaimedVerifiedStatus
1DistillAVWER1.4—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)4.28—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)8.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer TransducerWER (%)3.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Conformer Transducer (German)WER (%)8.98—Unverified